# bicorAndPvalue: Calculation of biweight midcorrelations and associated... In WGCNA: Weighted Correlation Network Analysis

 bicorAndPvalue R Documentation

## Calculation of biweight midcorrelations and associated p-values

### Description

A faster, one-step calculation of Student correlation p-values for multiple biweight midcorrelations, properly taking into account the actual number of observations.

### Usage

```bicorAndPvalue(x, y = NULL,
use = "pairwise.complete.obs",
alternative = c("two.sided", "less", "greater"),
...)
```

### Arguments

 `x` a vector or a matrix `y` a vector or a matrix. If `NULL`, the correlation of columns of `x` will be calculated. `use` determines handling of missing data. See `bicor` for details. `alternative` specifies the alternative hypothesis and must be (a unique abbreviation of) one of `"two.sided"`, `"greater"` or `"less"`. the initial letter. `"greater"` corresponds to positive association, `"less"` to negative association. `...` other arguments to the function `bicor`.

### Details

The function calculates the biweight midcorrelations of a matrix or of two matrices and the corresponding Student p-values. The output is not as full-featured as `cor.test`, but can work with matrices as input.

### Value

A list with the following components, each a marix:

 `bicor` the calculated correlations `p` the Student p-values corresponding to the calculated correlations `Z` Fisher transform of the calculated correlations `t` Student t statistics of the calculated correlations `nObs` Numbers of observations for the correlation, p-values etc.

### Author(s)

Peter Langfelder and Steve Horvath

### References

Peter Langfelder, Steve Horvath (2012) Fast R Functions for Robust Correlations and Hierarchical Clustering. Journal of Statistical Software, 46(11), 1-17. https://www.jstatsoft.org/v46/i11/

`bicor` for calculation of correlations only;

`cor.test` for another function for significance test of correlations

### Examples

```# generate random data with non-zero correlation
set.seed(1);
a = rnorm(100);
b = rnorm(100) + a;
x = cbind(a, b);
# Call the function and display all results
bicorAndPvalue(x)
# Set some components to NA
x[c(1:4), 1] = NA
corAndPvalue(x)
# Note that changed number of observations.
```

WGCNA documentation built on April 23, 2022, 1:06 a.m.